For a number of reasons (congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few), the importance of walking and bicycling as transportation options will likely continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used efficiently, accurate models sensitive to key policy variables are needed to support longrange planning and project evaluation. This project attempts to synthesize and advance the state of the art in nonmotorized mode choice modeling. This project proposes a more complete mode choice behavioral framework that acknowledges the importance of attributes along the specific walk and bike routes that travelers are likely to consider. The proposed framework will then be applied to a revealed preference travel datasets collected in Portland, Oregon. Measurement of nonmotorized trip distance/time, built environment, trip/tour, and attitude attributes as well as mode availability and model structure will be addressed explicitly. Route and mode choice models will be specified using discrete choice techniques.